A system and method of constructing a machine learning workflow by using machine learning suggestions derived from determining path lengths in a plurality of existing workflows, assigning a frequency threshold for each path and determining a probability for each path. This information is utilized to determine transpositions and deletions between paths that can be used as training for a machine learning algorithm that will suggest to the user which operators to put in a new machine learning workflow.
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2. The method as in claim 1, wherein said transpositions between rows and columns in a path are based on individual operators inside said alignment grid.
3. The method as in claim 1, wherein said transpositions between rows and columns in a path are based on sets of operators inside said alignment grid.
4. The method as in claim 1, further comprising the step of further adjusting said alignment grid based on additional parameters.
5. The method as in claim 1, further comprising the step of further adjusting said alignment grid to only show the path with a highest probability of occurrence of an individual path in a flow.
6. The method as in claim 1, further comprising the step of displaying said alignment grid and said calculated computer executed machine learning composite workflow path on a user interface.
7. The method as in claim 6, wherein said user interface allows a user to manually modify said alignment grid.
9. The system of claim 8, wherein said transpositions between rows and columns in a path are based on individual operators inside said alignment grid.
10. The system of claim 8, wherein said transpositions between rows and columns in a path are based on sets of operators inside said alignment grid.
11. The system of claim 8, further comprising the step of further adjusting said alignment grid based on additional parameters.
12. The system of claim 8, further comprising the step of further adjusting said alignment grid to only show the path with a highest probability of occurrence of an individual path in a flow.
13. The system of claim 8, further comprising the step of displaying said alignment grid and said calculated computer executed machine learning composite workflow path on a user interface.
14. The system of claim 13, wherein said user interface allows a user to manually modify said alignment grid.
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December 9, 2020
December 10, 2024
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